I\'d like to use principal component analysis (PCA) for dimensionality reduction.Does numpy or scipy already have it, or do I have to roll my own using numpy.linalg.eigh?
After doing some processing on an audio or image array, it needs to be normalized within a r开发者_运维百科ange before it can be written back to a file.This can be done like so:
I would like to delete selected columns in a numpy.array . This is what I do: n [397]: a = array([[ NaN,2.,3., NaN],
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I want to solve a set of equations, linear, or sometimes quadrati开发者_运维技巧c. I don\'t have a specific problem, but often, I have been in this situation often.
I\'m trying to recreate this graph: ... and this table: ... using this set of equations: It has to include these methods:
I tried using minimize function in scipy packages like below code When I use jac option = approx_fprime, iteration is 0 and optimization doesn\'t work.
I have a battery voltage data with respect to Datetime, collected data for one month I need to find out the number of cycles of battery hers is my data https://docs.开发者_运维百科google.com/spreadshe
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